We propose to enhance the data consistency and integrity of oversight and tracking systems for human subjects research at Mayo Foundation. Our specific aims include: 1) a comprehensive information modeling exercise to understand the interrelationships and dependencies of administrative and clinical data elements related to human subjects research oversight; 2) building common application components that will simplify the creation of research protocols, IRB application, research subject enrollment and consent, and administrative tracking; 3) providing full text and natural language processing based indices to project abstracts, applications, minutes, and administrative notes, to facilitate the authorized searching and retrieval of materials human subject related to human subject review; and 4) coordinating the information model, modular software tools, and textual indexing, as preliminary work for a competitive informatics proposal for adverse event recognition, pattern detection, and the consistent recording of drugs, devices and outcomes measures.